Ghasemi M.R., J. Ignatius, S. Lozano, A. Emrouznejad, A. Hatamimarbini (2015) A fuzzy expected value approach under generalized data envelopment analysis, Knowledge-Based Systems, 89: 148–159.

Ghasemi M.R., J. Ignatius, S. Lozano, A. Emrouznejad, A. Hatamimarbini (2015) A fuzzy expected value approach under generalized data envelopment analysis, Knowledge-Based Systems, 89: 148–159.

Fuzzy data envelopment analysis (DEA) models emerge as another class of DEA models to account for imprecise inputs and outputs for decision making units (DMUs). Although several approaches for solving fuzzy DEA models have been developed, there are some drawbacks, ranging from the inability to provide satisfactory discrimination power to simplistic numerical examples that handles only triangular fuzzy numbers or symmetrical fuzzy numbers. To address these drawbacks, this paper proposes a fuzzy expected generalized DEA model, which can treat fuzzy expected CCR, fuzzy expected BCC, and fuzzy expected FDH models in a unified way that handles both symmetrical and asymmetrical fuzzy numbers. We also considered super-efficiency evaluation problems, which is always feasible and it can be suggested as a way in dealing with infeasibility problems. The proposed method can be perceived as a form of aggregating solutions across a range of ?-levels. In order to illustrate the performance of the proposed method, it is first tested using two established numerical examples and compared with the results obtained from alternative methods. An application of energy dependency among 23 European Union (EU) member countries is further used to validate and describe the efficacy of our approach under asymmetric fuzzy numbers.

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Marra M., A. Emrouznejad. W. Ho and J.S. Edwards (2015), The value of indirect ties in citation networks: SNA analysis with OWA operator weights, Information Sciences, 314 (2015) 135.

Marra M., A. Emrouznejad. W. Ho and J.S. Edwards (2015), The value of indirect ties in citation networks: SNA analysis with OWA operator weights, Information Sciences, 314 (2015) 135.

This paper seeks to advance the theory and practice of the dynamics of complex networks in relation to direct and indirect citations. It applies social network analysis (SNA) and the ordered weighted averaging operator (OWA) to study a patent citations network. So far the SNA studies investigating long chains of patents citations have rarely been undertaken and the importance of a node in a network has been associated mostly with its number of direct ties. In this research OWA is used to analyse complex networks, assess the role of indirect ties, and provide guidance to reduce complexity for decision makers and analysts. An empirical example of a set of European patents published in 2000 in the renewable energy industry is provided to show the usefulness of the proposed approach for the preference ranking of patent citations.

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Gholami R., D. A.Higón, A. Emrouznejad (2015), “Hospital Performance: Efficiency or Quality? Can we have both with IT?,” Expert Systems with Applications, 42 (12) 5390–5400.

Gholami R., D. A.Higón, A. Emrouznejad (2015), “Hospital Performance: Efficiency or Quality? Can we have both with IT?,” Expert Systems with Applications, 42 (12) 5390–5400.

The influence of IT investment on hospital efficiency and quality are of great interest to healthcare executives as well as insurers. Few studies have examined how IT investments influence both efficiency and quality or whether there is an optimal IT investment level that influences both in the desired direction. Decision makers in healthcare wonder if there are tradeoffs between their pursuit of hospital operational efficiency and quality. Our study involving a 2-stage double bootstrap DEA analysis of 187 US hospitals over two years found direct effects of IT investment upon service quality and a moderating effect of quality upon operational efficiency. Further, our findings indicate a U-shaped relationship between IT investments and operational efficiency suggesting that IT investments have diminishing returns beyond a certain point.

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Arabi, B., S. Munisamy and A. Emrouznejad (2015), “A new Slacks-Based Measure of Malmquist-Luenberger Index in the Presence of Undesirable Outputs,” OMEGA, 51:29-37.

Arabi, B., S. Munisamy and A. Emrouznejad (2015), “A new Slacks-Based Measure of Malmquist-Luenberger Index in the Presence of Undesirable Outputs,” OMEGA, 51:29-37.

In the majority of production processes, noticeable amounts of bad byproducts or bad outputs are produced. The negative effects of the bad outputs on efficiency cannot be handled by the standard Malmquist index to measure productivity change over time. Toward this end, the Malmquist-Luenberger index (MLI) has been introduced, when undesirable outputs are present. In this paper, we introduce a Data Envelopment Analysis (DEA) model as well as an algorithm, which can successfully eliminate a common infeasibility problem encountered in MLI mixed period problems. This model incorporates the best endogenous direction amongst all other possible directions to increase desirable output and decrease the undesirable outputs at the same time. A simple example used to illustrate the new algorithm and a real application of steam power plants is used to show the applicability of the proposed model.

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Osman, I. H., A. L. Anouze and A. Emrouznejad (2015). Handbook of Research on Strategic Performance Management and Measurement Using Data Envelopment Analysis. IGI Global, USA, ISBN: 978-1-4666-4474-8.

Osman, I. H., A. L. Anouze and A. Emrouznejad (2015). Handbook of Research on Strategic Performance Management and Measurement Using Data Envelopment Analysis. IGI Global, USA, ISBN: 978-1-4666-4474-8.

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Emrouznejad A. and E. Thanassoulis (2015). Introduction to Performance Improvement Management Software (PIM-DEA), in Osman et al. (Eds.) Handbook of Research on Strategic Performance Management and Measurement Using Data Envelopment Analysis: 256-275. IGI Global, USA.

Emrouznejad A. and E. Thanassoulis (2015).  Introduction to Performance Improvement Management Software (PIM-DEA), in Osman et al. (Eds.) Handbook of Research on Strategic Performance Management and Measurement Using Data Envelopment Analysis: 256-275. IGI Global, USA.

 This chapter provides information on the use of Performance Improvement Management Software (PIM-DEA[1]). This advanced DEA software enables you to make the best possible analysis of your data, using the latest theoretical developments in Data Envelopment Analysis (DEA). PIM-DEA software gives you the capacity to assess efficiency and productivity, set targets, identify benchmarks and much more allowing you to truly manage the performance of organizational units. PIM-DEA is easy to use and powerful and it has an extensive range of the most up-to-date DEA models and which can handle large sets of data.

[1] For latest information please see: www.DEAsoftware.co.uk

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Emrouznejad A. and E. Cabanda (2015). Introduction to Data Envelopment Analysis and its applications, in Osman et al. (Eds.) Handbook of Research on Strategic Performance Management and Measurement Using Data Envelopment Analysis: 235-255. IGI Global, USA.

Emrouznejad A. and E. Cabanda (2015).  Introduction to Data Envelopment Analysis and its applications, in  Osman et al. (Eds.) Handbook of Research on Strategic Performance Management and Measurement Using Data Envelopment Analysis: 235-255. IGI Global, USA.

 This chapter provides the theoretical foundation and background on data envelopment analysis (DEA) method and some variants of basic DEA models and applications to various sectors. Some illustrative examples, helpful resources on DEA including DEA software package are also presented in this chapter. DEA is useful for measuring relative efficiency for variety of institutions and has its own merits and limitations. This chapter concludes that DEA results should be interpreted with much caution to avoid giving wrong signals and providing inappropriate recommendations.

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Emrouznejad, A. R. Banker, A.L.M Lopes, M. R. de Almeida (2014) “Data Envelopment Analysis in the Public Sector”. Socio-Economic Planning Sciences, 48 (1): 2-3.

Emrouznejad, A. R. Banker, A.L.M Lopes, M. R. de Almeida (2014) “Data Envelopment Analysis in the Public Sector”. Socio-Economic Planning Sciences, 48 (1): 2-3.

Since its introduction in 1978, Data Envelopment Analysis (DEA) has become one of the preeminent non-parametric methods for measuring efficiency and productivity of Decision Making Units (DMUs). DEA models are now employed routinely in areas that range from assessment of public sectors such as hospitals and health care systems, schools and universities to private sectors such as banks and financial institutions. The advantage of DEA is to accommodate multiple inputs and multiple outputs for measuring the relative efficiencies of a set of homogeneous DMUs.  DEA does not require that output and input prices be available for this analysis, which is a significant advantage for public sector applications where such prices are not available.

The scope of this issue was extended beyond that of just the papers presented at the conference via an open invitation to the broader academic community working in the area of theory and applications of efficiency and productivity analysis. Papers were included in the special issue after a rigorous refereeing process, and represent only a small fraction of the total number of submitted manuscripts; there were 41 submissions to this issue.

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Matin, R. K., G.R. Amin and A. Emrouznejad (2014), A Modified Semi-Oriented Radial Measure for target setting with negative data, Measurement 54: 152–158.

Matin, R. K., G.R. Amin and A. Emrouznejad (2014), A Modified Semi-Oriented Radial Measure for target setting with negative data, Measurement 54: 152–158.

Over the last few years Data Envelopment Analysis (DEA) has been gaining increasing popularity as a tool for measuring efficiency and productivity of Decision Making Units (DMUs). Conventional DEA models assume non-negative inputs and outputs. However, in many real applications, some inputs and/or outputs can take negative values. Recently, Emrouznejad et al. (2010a) introduced a Semi-Oriented Radial Measure (SORM) for modelling DEA with negative data. This paper points out some issues in target setting with SORM models and introduces a modified SORM approach. An empirical study in bank sector demonstrates the applicability of the proposed model.

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Gattoufi S., G. R. Amin, A. Emrouznejad (2014). “A new inverse DEA method for merging banks.” IMA Journal of Management Mathematics, 25: 73–87.

Gattoufi S., G. R. Amin, A. Emrouznejad (2014). “A new inverse DEA method for merging banks.” IMA Journal of Management Mathematics, 25: 73–87.

This study suggests a novel application of Inverse Data Envelopment Analysis (InvDEA) in strategic decision making about mergers and acquisitions in banking. The conventional DEA assesses the efficiency of banks based on the information gathered about the quantities of inputs used to realize the observed level of outputs produced. The decision maker of a banking unit willing to merge/acquire another banking unit needs to decide about the inputs and/or outputs level if an efficiency target for the new banking unit is set. In this paper, a new InvDEA-based approach is developed to suggest the required level of the inputs and outputs for the merged bank to reach a predetermined efficiency target. This study illustrates the novelty of the proposed approach through the case of a bank considering merging with or acquiring one of its competitors to synergize and realize higher level of efficiency. A real data set of 42 banking units in Gulf Corporation Council countries is used to show the practicality of the proposed approach.

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